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    Archives

    The Research archive provides access to all Research articles published in past issues of Communications of the ACM.

    June 2021


    From Communications of the ACM

    Simba: Scaling Deep-Learning Inference with Chiplet-Based Architecture

    Simba

    This work investigates and quantifies the costs and benefits of using multi-chip-modules with fine-grained chiplets for deep learning inference, an application domain with large compute and on-chip storage requirements.

    Yakun Sophia Shao, Jason Cemons, Rangharajan Venkatesan, Brian Zimmer, Matthew Fojtik, Nan Jiang, Ben Keller, Alicia Klinefelter, Nathaniel Pinckney, Priyanka Raina, Stephen G. Tell, Yanqing Zhang, William J. Dally, Joel Emer, C. Thomas Gray, Brucek Khailany, Stephen W. Keckler | June 2021

    From Communications of the ACM

    In-Sensor Classification With Boosted Race Trees

    In-Sensor Classification With Boosted Race Trees

    We demonstrate the potential of a novel form of encoding, race logic, in which information is represented as the delay in the arrival of a signal.

    Georgios Tzimpragos, Advait Madhavan, Dilip Vasudevan, Dmitri Strukov, Timothy Sherwood | June 2021

    From Communications of the ACM

    Technical Perspective: Race Logic Presents a Novel Form of Encoding

    "In-Sensor Classification With Boosted Race Trees," by Georgios Tzimpragos, et al., proposes a surprising, novel, and creative approach to post-Moore's Law computing by rethinking the digital/analog boundary.

    Abhishek Bhattacharjee | June 2021

    From Communications of the ACM

    Technical Perspective: A Chiplet Prototype System for Deep Learning Inference

    "Simba," by Yakun Sophia Shao, et al., presents a scalable deep learning accelerator architecture that tackles issues ranging from chip integration technology to workload partitioning and non-uniform latency effects on deep neural…

    Natalie Enright Jerger | June 2021